A meta-analysis to infer generic predator functional response
A macro-ecological approach to predators' functional response
Species interactions are classically derived from the law of mass action: the probability that, for example, a predation event occurs is proportional to the product of the density of the prey and predator species. In order to describe how predator and prey species populations grow, is then necessary to introduce functional response, describing the intake rate of a consumer as a function of food (e.g. prey) density.
Linear functional responses shapes are typically introduced in the ecological modeling of population dynamics for both predator-prey and mutualistic systems [1,2]. Recently some works have proposed alternatives to the classic approach for mutualistic systems [3,4], both because cooperative interactions also model effect not directly related to mass action  and for analytical tractability [4,5].
In this work  the authors challenge the classic modeling of functional response also for predator-prey systems. In particular, they use a meta-analysis of several observational studies of predator-prey ecosystems to infer a generic predator functional response, fitting a phenomenological generalization of the mass-action law. Using advanced statistical analysis, they show that the functional response obtained from data is clearly different from the mass-action assumption. In fact, they found that it scales sub-linearly as the square root of the ratio between predator and prey biomass. They further argue that, from a macro-ecological point of view, using such a phenomenological relationship might be more valuable than relying on various mechanistic functional response formulations.
The manuscript thus provides an interesting different perspective on how to approach predator-prey modelling and for this reason, I have recommended the work for PCI Ecology.
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 García-Algarra, J., Galeano, J., Pastor, J. M., Iriondo, J. M., and Ramasco, J. J. (2014). Rethinking the logistic approach for population dynamics of mutualistic interactions. Journal of Theoretical Biology, 363, 332–343. doi: 10.1016/j.jtbi.2014.08.039
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 Barbier, M., Wojcik, L., and Loreau, M. (2020). A macro-ecological approach to predators’ functional response. BioRxiv, 832220, ver. 4 recommended and peer-reviewed by Peer Community in Ecology. doi: 10.1101/832220
Samir Simon Suweis (2020) A meta-analysis to infer generic predator functional response. Peer Community in Ecology, 100051. 10.24072/pci.ecology.100051
Evaluation round #2
DOI or URL of the preprint: https://doi.org/10.1101/832220
Version of the preprint: 2
Author's Reply, 04 Mar 2020
Decision by Samir Simon Suweis, 17 Feb 2020
thanks for the resubmission. After reading your revised manuscript and your response to reviewers comments, I think that the concerns have indeed been addressed very satisfactorily, and I would now like to suggest very minor revisions following some of the comments of one of the reviewers that I highlight here.
Once they are done, I will post my recommendation for the updated preprint.
Besides the typos highlighted at the end of the review, I think that the following points raised by the reviewer should be considered:
1) Please add a short paragraph at the introduction explicitly stating "why knowledge of an over-arching functional response is of an importance. What understanding it provides and what kind of predictions it can be used for"
2) Justification of eq. 6. Why it is reasonable to assume that the constant A is scale independent? I add a further comment on this point. In the text you write: We investigate a power-law dependence of predation losses (see discussion in Box 1). However, in Box 1 there is no an explicit connection between the power law functional shape and Eqs. (11). This is connected to the comment of the reviewer "nowhere explain why you have chosen the power-law functional form for your general..."
3) Answer to reviewers criticism on footnote 3
4) If it is possible, I think that it is worthwhile to investigate the reviewer suggestion: "I am wondering whether the scalings you derive in section 3.3 are actually supported by your simulations used to develop Figures 3 and 4. Could you extract data on Pi, Bi and B(i+1) at equilibrium from your simulations and show how they relate to your formulas (17) and (18)?"
Additional requirements of the managing board:
As indicated in the 'How does it work?’ section and in the code of conduct, please make sure that:
-Data are available to readers, either in the text or through an open data repository such as Zenodo (free), Dryad or some other institutional repository. Data must be reusable, thus metadata or accompanying text must carefully describe the data.
-Details on quantitative analyses (e.g., data treatment and statistical scripts in R, bioinformatic pipeline scripts, etc.) and details concerning simulations (scripts, codes) are available to readers in the text, as appendices, or through an open data repository, such as Zenodo, Dryad or some other institutional repository. The scripts or codes must be carefully described so that they can be reused.
-Details on experimental procedures are available to readers in the text or as appendices.
-Authors have no financial conflict of interest relating to the article. The article must contain a "Conflict of interest disclosure" paragraph before the reference section containing this sentence: "The authors of this preprint declare that they have no financial conflict of interest with the content of this article." If appropriate, this disclosure may be completed by a sentence indicating that some of the authors are PCI recommenders: “XXX is one of the PCI XXX recommenders.”
Reviewed by Ludek Berec, 06 Feb 2020
Evaluation round #1
DOI or URL of the preprint: 10.1101/832220
Version of the preprint: 1
Author's Reply, 16 Jan 2020
Decision by Samir Simon Suweis, 19 Dec 2019
I invite you to revise the paper at the light of the reviewers' reports. I think that the manuscript will be improved if you take seriously and discuss reviewers' comments and suggestions.